Business intelligence and PEBKAC

Context

I’m currently sitting in the QANTAS club at Canberra airport waiting to return home after a week at ANU working on the PhD (being done through ANU). I decided to read a copy of CIO magazine while having brunch. In doing so I came across this article (Rodgers, 2009) title “Mind your own Business Intelligence.

This caught my eye because it mentions business intelligence. Business intelligence is very close to, for some it encompasses, the kind of work we’re starting in the Indicators project.

Business intelligence has dropped from the top 10

What interested me was this paragraph from the article

Perhaps even more surprising, however, was the fact that business intelligence dropped out of the top 10 items on CIOs’ agendas next year. Getting the right information to the right people at the right time for the right cost is what it takes to succeed in today’s business environment. Perhaps business intelligence sliding out of the top 10 is an indication of just how difficult BI is to achieve. BI is a moving target; it’s something that senior IT execs must constantly monitor and review to ensure that their organisation is getting the right information to key employees.

I find this interesting on two fronts:

  1. CIOs are losing interest in business intelligence.
  2. The slight touch of PEBKAC being implied as one of the problems.

PEBKAC

PEBKAC is an acronym devised by IT professionals as a code word for user error. i.e. the stupid user has made another mistake. PEBKAC expands out to Problem Exists Between Keyboard And Chair – i.e. the user. There is a tendency for IT folk to blame the user, instead of the technology.

The Wikipedia page on PEBKAC provides an important and interesting alternate perspective

Interface designers dismiss the blame on users for such trivial errors, arguing that a system that induces users to make mistakes is a badly designed one. By not taking human factors into consideration, its specification is incomplete and can make false or untested assumptions about the experience, knowledge and natural limits of their expected audience. Since the design lacks a major source of requirements, the resulting system will not be tailored to its purpose. The misunderstanding of the system that leads to the error is fault of the designer, not the user.

i.e. the problem is that system is designed for people to use correctly.

From this perspective, perhaps the problem with business intelligence isn’t that IT execs haven’t been constantly monitoring and reviewing the use of business intelligence to ensure that “their organisation is getting the right information to the key employees”.

Perhaps the technology the processes IT are using around business intelligence are broken. Perhaps they have not taken “human factors into consideration, its specification is incomplete and can make false or untested assumptions about the experience, knowledge and natural limits of their expected audience”.

I agree that business intelligence is really difficult, I believe most of its problems is that the tools and processes used to implement BI within organisations is broken.

The history of technology mediated learning

In an earlier post I argued that there is a highly visible hype cycle around e-learning/technology mediated learning. I think the same hype cycle exists in broader technology. This hype cycle is more closely aligned with Birnbaum than that of Gartner.

The four (grown from three) phases in the cycle I use are:

  1. Technological spark – some new technology sparks interest, or enables new capabilities, solves an existing problem.
  2. Growing revolution – a collection of folk find the spark important and a “club” grows around the technology building it up as the saviour of all.
  3. Minimal impact – oops, it didn’t really make all that much difference, not many folk used it. Oh well.
  4. Resolution of dissonance – the smart folk who pushed the revolution have to explain away why they were wrong. They can’t blame themselves. So they blame the users.

I think business intelligence may be getting into stage 3. Just like LMSes. But with LMSes, everyone is now going open source. The next fad.

References

Birnbaum, R. (2000). Management Fads in Higher Education: Where They Come From, What They Do, Why They Fail. San Francisco, Jossey-Bass.

Rodgers, M. (2009). Mind your own Business Intelligence. CIO. Summer 2009/2010: 4.

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